Observability of lensing of gravitational waves from massive black hole binaries with Laser Interferometer Space Antenna

ORAL

Abstract

The gravitational waves emitted by massive black hole binaries in the LISA band can be lensed. Wave-optics effects in the lensed signal are crucial when the Schwarzschild radius of the lens is smaller than the wavelength of the radiation. These frequency-dependent effects can enable us to infer the lens parameters, possibly with a single detection alone. In this work, we assess the observability of wave-optics effects with LISA by performing an information-matrix analysis using analytical solutions for both point-mass and singular isothermal sphere lenses. We use gravitational-waveform models that include the merger, ringdown, higher harmonics, and aligned spins to study how waveform models and source parameters affect the measurement errors in the lens parameters. We find that previous work underestimated the observability of wave-optics effects and that LISA can detect lensed signals with higher impact parameters and lower lens masses. Comparing lens populations obtained from the Press-Schechter mass function and the measured velocity function based on the SDSS, we find that the probability of observing wave-optics effects is highly sensitive to the abundance of low-mass lenses such as late-type galaxies and sub-halos and that this probability can be significantly higher than the probability of observing strong lensing.

*M.Ç., R.C., and E.B. are supported by NSF Grants No. AST-2006538, PHY-2207502, PHY-090003 and PHY20043, and NASA Grants No. 19-ATP19-0051, 20-LPS20- 0011 and 21-ATP21-0010. M.K. and L.J. were supported by NSF Grant No. 1818899 and the Simons Foundation. M.Ç. is also supported by Johns Hopkins University through the Rowland Research Fellowship. This work was carried out at the Advanced Research Computing at Hopkins (ARCH) core facility (rockfish.jhu.edu), which is supported by the NSF Grant No. OAC-1920103. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC, visualization, database, or grid resources that have contributed to the research results reported within this paper.

Publication: https://arxiv.org/abs/2206.02803 (submitted to PRD)

Presenters

  • Mesut Çaliskan

    • Johns Hopkins University

Authors

  • Mesut Çaliskan

    • Johns Hopkins University
  • Lingyuan Ji

    • University of California, Berkeley
  • Roberto Cotesta

    • Johns Hopkins University
  • Emanuele Berti

    • Johns Hopkins University
  • Marc P Kamionkowski

    • Johns Hopkins University
  • Sylvain Marsat

    • Universíté de Toulouse